|Publication number||US8156154 B2|
|Application number||US 11/702,391|
|Publication date||Apr 10, 2012|
|Filing date||Feb 5, 2007|
|Priority date||Feb 5, 2007|
|Also published as||CN101606174A, CN101606174B, EP2118841A1, EP2118841A4, US20080189312, WO2008097727A1|
|Publication number||11702391, 702391, US 8156154 B2, US 8156154B2, US-B2-8156154, US8156154 B2, US8156154B2|
|Inventors||Viktoriya Taranov, Daniel E. Kogan, Patrick C. Miller, Michal K. Piaseczny, Gerhard Schobbe|
|Original Assignee||Microsoft Corporation|
|Export Citation||BiBTeX, EndNote, RefMan|
|Patent Citations (21), Non-Patent Citations (8), Referenced by (10), Classifications (4), Legal Events (3)|
|External Links: USPTO, USPTO Assignment, Espacenet|
A managed taxonomy system attempts to manage a taxonomy for an application, device or network. A taxonomy attempts to define a common or standard vocabulary for interacting with an application or system. The standard vocabulary may then be used for different applications, such as classification applications, search applications, tagging applications, and so forth. To create a standard vocabulary, managed taxonomy systems attempt to build and manage a highly structured and formalized hierarchy of standard vocabulary terms. Managed taxonomy systems, however, are typically difficult to maintain and manage, particularly across heterogeneous systems that are typically not designed to use the same vocabulary. Consequently, there may be a need for improved techniques for managing vocabulary terms and relationships for a managed taxonomy system.
This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Various embodiments may be generally directed to techniques to manage vocabulary terms for a managed taxonomy system. In particular, some embodiments may be directed to techniques for managing vocabulary terms for a managed taxonomy system across heterogeneous resource domains. In one embodiment, for example, an apparatus such as a managed taxonomy system may include a vocabulary management module to manage a taxonomy of formal and informal vocabulary terms organized in a hierarchical structure. The managed taxonomy system may further include a vocabulary association module to associate a vocabulary term with multiple resources from different resource domains, and store the resource associations or resource relationships in a central database. The different resource domains may represent different or heterogeneous systems, devices, or applications. In this manner, a single managed taxonomy system may be used to manage resource associations or resource relationships uniformly across different resource domains, thereby allowing more efficient searching for resources, as well as other applications. Other embodiments are described and claimed.
Various embodiments may comprise one or more elements. An element may comprise any feature, characteristic, structure or operation described in connection with an embodiment. Examples of elements may include hardware elements, software elements, physical elements, or any combination thereof. Although an embodiment may be described with a limited number of elements in a certain arrangement by way of example, the embodiment may include more or less elements in alternate arrangements as desired for a given implementation. It is worthy to note that any references to “one embodiment” or “an embodiment” are not necessarily referring to the same embodiment.
Various embodiments may be generally directed to techniques to manage vocabulary terms for a managed taxonomy system. A taxonomy may generally refer to a structure, method or technique for classifying information or data. The vocabulary terms may include various types, including formal vocabulary terms and informal vocabulary terms. A managed taxonomy may refer to a taxonomy that is managed in accordance with a formal set of rules, procedures or guidelines for a given system. A managed taxonomy system may be any system arranged to store, process, communicate, and otherwise manage a defined taxonomy for an electronic system or collection of electronic systems.
More particularly, some embodiments may be directed to techniques for managing vocabulary terms for a managed taxonomy system across heterogeneous resource domains. A resource domain may refer to a logical or physical segmentation between groups or collections of resources. A resource may refer to a discrete or single set of data or data object. Examples of resources may include files, media files, text files, audio files, image files, video files, web pages, data items, and so forth. Typically, different resource domains are managed by different entities, such as different businesses, companies, systems, devices, application programs, and so forth. Further, each entity typically implements a unique managed taxonomy management system to define and manage its own vocabulary or taxonomy, and uses proprietary vocabulary terms for various knowledge-based applications, such as classification applications, search applications, tagging applications, and so forth. Consequently, such knowledge-based applications may be limited to a single resource domain utilizing a particular vocabulary. For example, a knowledge-based search application using a given vocabulary term may be limited to retrieving resources from a single resource domain, even though there may be resources related to the vocabulary term from other resource domains. Even when different resource domains use the same vocabulary term, the disparate managed taxonomy systems are typically not integrated, and therefore are unable to access resources associated with the common vocabulary term across the different resource domains.
To solve these and other problems, various embodiments may implement a uniform managed taxonomy system to manage vocabulary terms across heterogeneous or different resource domains. In one embodiment, for example, a managed taxonomy system may implement a vocabulary management module to manage a taxonomy of formal and informal vocabulary terms organized in a hierarchical structure. The managed taxonomy system may further include a vocabulary association module to associate a vocabulary term with multiple resources from different resource domains, and store the resource associations or resource relationships in a central database. In this manner, a single managed taxonomy system may be used to manage resource associations or resource relationships uniformly across different resource domains. Centralized management of a taxonomy across heterogeneous systems provides a centralized and shared database of vocabulary terms and relationships, which may be used for various knowledge-based applications such as classification applications, search applications, tagging applications, and so forth. By having a common set of vocabulary terms that can apply across various heterogeneous systems, and a central store for managing the relationships, it becomes possible to now relate otherwise disconnected systems with each other.
As shown in
In one embodiment, for example, a resource domain 130-1 may represent multiple application programs 132-1-p. Each of the application programs 132-1-p may manage, or be coupled to, a respective resource set 160-1-p, with each resource set 160-1-p representing multiple resources or resource objects. Application programs generally may allow a user to accomplish one or more specific tasks. Examples of application programs may include, without limitation, one or more messaging applications (e.g., telephone, voicemail, facsimile, e-mail, IM, SMS, MMS, video conferencing), a web browser application, personal information management (PIM) applications (e.g., contacts, calendar, scheduling, tasks), word processing applications, spreadsheet applications, database applications, media applications (e.g., video player, audio player, multimedia player, digital camera, video camera, media management), gaming applications, and so forth. In various implementations, the application programs may provide one or more graphical user interfaces (GUIs) to communicate information between the application program and a user. By way of example only, assume the application program 132-1 is implemented as WINDOWS® MEDIA PLAYER made by MICROSOFT® CORPORATION, while the application program 132-2 is implemented as MICROSOFT OUTLOOK® made by MICROSOFT CORPORATION. The embodiments, however, are not limited to these examples.
In one embodiment, for example, a resource domain 130-2 may represent multiple enterprise systems 134-1-q. An enterprise system is typically an information technology (IT) or knowledge system implemented for a specific business entity. Enterprise systems 134-1-q may represent multiple enterprise systems implemented for the same entity, or different entities. Each of the enterprise systems 134-1-q may manage, or be coupled to, a respective resource set 170-1-q, with each resource set 170-1-q representing multiple resources or resource objects.
In one embodiment, for example, a resource domain 130-3 may represent multiple devices 136-1-r. Devices 136-1-r may represent any type of electronic device, such as (he examples provided for the node 110 as previously described. Each of the devices 132-1 -r may manage, or be coupled to. a respective resource set 180-1-r, with each resource set 180-1-r representing multiple resources or resource objects.
In various embodiments, each of the resource domains 130-1, 130-2 and 130-3 and possibly their sub-domains typically maintain a separate set of resources. For example, application program 132-1 implemented as WINDOWS MEDIA PLAYER® may have a set of resources in the form of media files, while application program 132-2 implemented as MICROSOFT OUTLOOK® may have a set of resource in the form of contact items, calendar items, task items, memo items, email items, and so forth. Assume a first user tags a media file with a product name, while a second user tags an email item with a product name. In conventional systems, a search by product name would need to be implemented separately for respective application programs 132-1, 132-2. Further, the search results for both may need to be correlated to determine whether the product name refers to the same product. Such a process may be limiting and tedious for a user, and the problem becomes exponentially worse as the number of application programs 132-1-p increases.
In order to reduce such problems, the knowledge system 150 may include a node 110 implementing a managed taxonomy system 100 that may be used across some or all of the resource domains 130-1-s. The node 110 may represent any suitable electronic device or system arranged to implement the managed taxonomy system 100, such as a processing system, computer, server, work station, appliance, terminal, personal computer, laptop, ultra-laptop, handheld computer, minicomputer, mainframe computer, distributed computing system, multiprocessor systems, processor-based systems, consumer electronics, programmable consumer electronics, personal digital assistant, television, digital television, set top box, telephone, mobile telephone, cellular telephone, handset, wireless access point, base station, subscriber station, mobile subscriber center, radio network controller, router, hub, gateway, bridge, switch, machine, or combination thereof. The embodiments are not limited in this context.
In various embodiments, the managed taxonomy system 100 may represent any system arranged to store, process, communicate, and otherwise manage a defined or managed taxonomy for an electronic system or collection of electronic systems. As shown in
As used herein the term “module” may include any structure implemented using hardware elements, software elements, or a combination of hardware and software elements. In one embodiment, for example, the modules described herein are typically implemented as software elements stored in memory and executed by a processor to perform certain defined operations. It may be appreciated that the defined operations, however, may be implemented using more or less modules as desired for a given implementation. It may be further appreciated that the defined operations may be implemented using hardware elements based on various design and performance constraints. The embodiments are not limited in this context.
In various embodiments, the managed taxonomy system 100 may be used to manage any defined taxonomy. An entity such as a company, business or enterprise may use different application programs to manage information across the entity. Often the vocabulary and taxonomy for an entity varies with the type of entity and a given set of products and/or services. In one embodiment, for example, the managed taxonomy system 100 may be used to manage specific vocabulary terms for entities operating within a computing and/or communications environment, sometimes referred to as an online environment. In this context such vocabulary terms are sometimes referred to as “metadata.” Metadata may refer to structured, encoded data that describe characteristics of information-bearing entities to aid in the identification, discovery, assessment, and management of the described entities. Generally, a set of metadata describes a single object or set of data, called a resource. Metadata may be of particular use for such applications as information retrieval, information cataloging, and the semantic web. For example, the vocabulary terms may be metadata used as tags for tagging operations. A tag is a relevant keyword or term associated with or assigned to a piece of information or resource. The tag may thus describe the resource and enable keyword-based classification of the resource.
One problem with conventional managed taxonomy systems is integrating the vocabulary informality typically associated with tagging operations and other “Web 2.0” applications with the vocabulary formality typically used for business and enterprise systems. Tags are usually chosen informally and personally by the author/creator of the item, and are not typically part of some formally defined classification scheme. Rather, tags are typically used in dynamic, flexible, automatically generated internet taxonomies for online resources, such as computer files, web pages, digital images, and internet bookmarks. A business or enterprise, however, typically defines its vocabulary using a very specific and formal scientific ontology. A managed taxonomy system for a business or enterprise may therefore face considerable challenges in balancing the creativity of growth with the certainty needed in a business environment.
Vocabulary structure for a system may be viewed as more of a continuum rather than a discrete series of binary choices. At one end of the continuum there is no managed vocabulary. People may associate keywords with a document, but there is no system in place to use them. Search consists solely of full text crawling. At the next level, the vocabulary is a flat list of keywords, which is a common well from which users can select a term. Depending on the infrastructure surrounding this vocabulary, you can still get some useful features out of the system. Different applications within the company can be speaking the same semantic language, allowing these different systems to communicate with each other. Another level is to track some sort of relationship between the various terms in the vocabulary. Yet another level is defining previous associations, such as equality relationships. The equality relationships may comprise business specific synonyms in the vocabulary pushed into a custom thesaurus or dictionary. This may be useful when a product moves through various incarnations with different names, or when two different development teams within an enterprise try and consolidate their individual vocabularies into a single shared vocabulary. Finally, the other end of the continuum may be an ontological vocabulary that adds named relationships to the vocabulary. Relationships like “competes with” or “makes” give an even greater amount of information to the rest of the system. It is at this point that you no longer need to know what you are searching for to find it. For example, a search may be performed for “back pain medication” without previously knowledge of particular back pain medications.
In various embodiments, the managed taxonomy system 100 attempts to operate within this vocabulary structure continuum. More particularly, the managed taxonomy system 100 attempts to provide a higher level of integration between the informal vocabulary terms generated by authors and creators of a resource (e.g., as used for tagging operations), with the formal vocabulary terms comprising part of a scientific ontology used to typically define a vocabulary for business or enterprise operations. The managed taxonomy system 100 may be designed with a hybrid approach to vocabulary management, with certain areas of the vocabulary that are highly structured, and other areas of the vocabulary that are managed as a flat list of keywords. For example, the vocabulary terms dealing with specific product groups and their associated products for a business may be relatively straightforward to place in hierarchies with defined relationships. Vocabulary terms dealing with specific general technologies, however, may be not be used enough inside a given business to warrant the additional overhead of managing them in anything other than a keyword list. This hybrid approach allows a business to start from a very loose freeform based system and grow towards a more structured and possibly process driven vocabulary as their needs and sophistication warrant. Most companies will be in this hybrid state, with sections of their vocabulary being very polished where the data either tends to be more easily structured, or where certain business segments demand it (e.g., company organizational charts, legal terms, marketing terms, and so forth), while other areas may be less structured with more keyword buckets and where relationships are derived through algorithmic analysis or end user suggestions.
Referring again to
In one embodiment, for example, the managed taxonomy system 100 may include the resource domain registration module 104. In order for a new resource domain 130-1-s to be managed by the managed taxonomy system 100, or use the managed taxonomy 112, the new resource domain 130-1-s should first register with the managed taxonomy system 100. Accordingly, the resource domain registration module 104 may be arranged to register a resource domain 130-1-s with the managed taxonomy system 100. Once registered, the resource domain 130-1-s may access the managed taxonomy 112 and various features offered by the managed taxonomy system 100. For example, the resource domain 130-1-s may use vocabulary association module 106 to perform tagging operations and store the created resource relationships 120-1-o in the vocabulary database 108.
In one embodiment, for example, the managed taxonomy system 100 may include the vocabulary association module 106. The vocabulary association module 106 may be arranged to associate a formal vocabulary term 114-1-m or informal vocabulary term 116-1-n with a resource, such as a resource from resource sets 160-1-p, 170-1-q or 180-1-r. The association operations are representative of tagging operations where a tag or metadata is associated with a given resource. For example, a data object such as a picture may be tagged with metadata such as a date, a time, a place, a photographer, an event, and so forth. Once a formal vocabulary term 114-1-m or informal vocabulary term 116-1-n has been stored in the vocabulary database 108, the vocabulary management module 102 may send a message to the vocabulary association module 106 notifying the vocabulary association module 106 of the formal vocabulary term 114-1-m or informal vocabulary term 116-1-n. A user interface or graphic user interface may be used to present a list of the formal vocabulary terms 114-1-m or informal vocabulary terms 116-1-n to a user. A user may select one or more of the formal vocabulary terms 114-1-m or informal vocabulary terms 116-1-n, relate or associate the selected the formal vocabulary term 114-1-m or informal vocabulary term 116-1-n with a resource, and return a user selected resource relationship 120-1-o to the vocabulary association module 106. The vocabulary association module 106 may store the resource relationship 120-1-o in the resource relationship list 118 of the vocabulary database 108.
In one embodiment, for example, the managed taxonomy system 100 may include the vocabulary database 108. Vocabulary database 108 may be used to store the managed taxonomy 112 and the resource relationship list 118 for the managed taxonomy system 100. In one embodiment, for example, the managed taxonomy 112 may be implemented as a hierarchical structure of various types, commonly displaying parent-child relationships. Although one embodiment may describe a managed taxonomy 112 in terms of a hierarchical structure or organization, the managed taxonomy 112 may also be implemented as other non-hierarchical structures having various topologies, such as network structures, organization of objects into groups or classes, alphabetical lists, keyword lists, and so forth. The embodiments are not limited in this context.
In one embodiment, for example, the vocabulary database 108 may also store resource relationships 120-1-o representing a relationship between a given vocabulary term and a particular resource. In some cases, the resource relationships 120-1-o may sometimes be referred to as “resource associations.” As used herein, the terms “resource relationship” and “resource association” have similar meanings, and are used interchangeably (collectively referred to as “resource relationship”).
The resource relationship 120-1-o may be created via vocabulary association module 106, and stored in the resource relationship list 118 of vocabulary database 108. Since the resource relationships 120-1-o may represent defined or tagged relationships between vocabulary terms from the managed taxonomy 112 as applied to different resource domains 130-1-s, the resource relationships 120-1-o may be used for various knowledge-based applications across heterogeneous resource domains 130-1-s. For example, a knowledge-based search application for a vocabulary term that is part of the managed taxonomy 112 may retrieve resources across the various resource domains 130-1-s based on the resource relationships 120-1-o stored in the resource relationship list 118 in the central vocabulary database 108.
As shown in
By way of example, assume that vocabulary term 206-4 represents a product name of “PRODUCT.” Further, assume that a first resource relationship 120-1 comprises a resource 208-1 representing a media file for a marketing presentation for the PRODUCT managed by the application program 132-1 implemented as the WINDOWS MEDIA PLAYER®. Assume that a second resource relationship 120-2 comprises a resource 208-2 representing a contact item for an author of the media file for the PRODUCT managed by the application program 132-2 implemented as the MICROSOFT OUTLOOK®. Assume that a third resource relationship 120-3 comprises a resource 208-3 representing a supplier contract for the PRODUCT managed by the enterprise system 134-1 as owned by the supplier. In general operation, a search application using the vocabulary term PRODUCT will return the media file 208-1, the contact item 208-2, and the supplier contract 208-3.
Operations for apparatus 100 may be further described with reference to one or more logic flows. It may be appreciated that the representative logic flows do not necessarily have to be executed in the order presented, or in any particular order, unless otherwise indicated. Moreover, various activities described with respect to the logic flows can be executed in serial or parallel fashion. The logic flows may be implemented using one or more elements of apparatus 100 or alternative elements as desired for a given set of design and performance constraints.
Various embodiments may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include any software element arranged to perform particular operations or implement particular abstract data types. Some embodiments may also be practiced in distributed computing environments where operations are performed by one or more remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
As shown in
In one embodiment, for example, the computer 910 may include one or more processing units 920. A processing unit 920 may comprise any hardware element or software element arranged to process information or data. Some examples of the processing unit 920 may include, without limitation, a complex instruction set computer (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a processor implementing a combination of instruction sets, or other processor device. In one embodiment, for example, the processing unit 920 may be implemented as a general purpose processor. Alternatively, the processing unit 920 may be implemented as a dedicated processor, such as a controller, microcontroller, embedded processor, a digital signal processor (DSP), a network processor, a media processor, an input/output (I/O) processor, a media access control (MAC) processor, a radio baseband processor, a field programmable gate array (FPGA), a programmable logic device (PLD), an application specific integrated circuit (ASIC), and so forth. The embodiments are not limited in this context.
In one embodiment, for example, the computer 910 may include one or more memory units 930 coupled to the processing unit 920. A memory unit 930 may be any hardware element arranged to store information or data. Some examples of memory units may include, without limitation, random-access memory (RAM), dynamic RAM (DRAM), Double-Data-Rate DRAM (DDRAM), synchronous DRAM (SDRAM), static RAM (SRAM), read-only memory (ROM), programmable ROM (PROM), erasable programmable ROM (EPROM), EEPROM, Compact Disk ROM (CD-ROM), Compact Disk Recordable (CD-R), Compact Disk Rewriteable (CD-RW), flash memory (e.g., NOR or NAND flash memory), content addressable memory (CAM), polymer memory (e.g., ferroelectric polymer memory), phase-change memory (e.g., ovonic memory), ferroelectric memory, silicon-oxide-nitride-oxide-silicon (SONOS) memory, disk (e.g., floppy disk, hard drive, optical disk, magnetic disk, magneto-optical disk), or card (e.g., magnetic card, optical card), tape, cassette, or any other medium which can be used to store the desired information and which can accessed by computer 910. The embodiments are not limited in this context.
In one embodiment, for example, the computer 910 may include a system bus 921 that couples various system components including the memory unit 930 to the processing unit 920. A system bus 921 may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, Peripheral Component Interconnect (PCI) bus also known as Mezzanine bus, and so forth. The embodiments are not limited in this context.
In various embodiments, the computer 910 may include various types of storage media. Storage media may represent any storage media capable of storing data or information, such as volatile or non-volatile memory, removable or non-removable memory, erasable or non-erasable memory, writeable or re-writeable memory, and so forth. Computer readable media may include storage media adapted for reading and writing to a computing system, such as the computing system architecture 900. Examples of computer readable media for computing system architecture 900 may include, but are not limited to, volatile and/or nonvolatile memory such as ROM 931 and RAM 932. Communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio-frequency (RF) spectrum, infrared and other wireless media. Combinations of the any of the above should also be included within the scope of computer readable media.
In various embodiments, the memory unit 930 includes computer storage media in the form of volatile and/or nonvolatile memory such as ROM 931 and RAM 932. A basic input/output system 933 (BIOS), containing the basic routines that help to transfer information between elements within computer 910, such as during start-up, is typically stored in ROM 931. RAM 932 typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit 920. By way of example, and not limitation,
The computer 910 may also include other removable/non-removable, volatile/nonvolatile computer storage media. By way of example only,
The drives and their associated computer storage media discussed above and illustrated in
The computer 910 may operate in a networked environment using logical connections to one or more remote computers, such as a remote computer 980. The remote computer 980 may be a personal computer (PC), a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer 910, although only a memory storage device 981 has been illustrated in
When used in a LAN networking environment, the computer 910 is connected to the LAN 971 through a network interface or adapter 970. When used in a WAN networking environment, the computer 910 typically includes a modem 972 or other technique suitable for establishing communications over the WAN 973, such as the Internet. The modem 972, which may be internal or external, may be connected to the system bus 921 via the user input interface 960, or other appropriate mechanism. In a networked environment, program modules depicted relative to the computer 910, or portions thereof, may be stored in the remote memory storage device. By way of example, and not limitation,
Some or all of the managed taxonomy system 100 and/or computing system architecture 900 may be implemented as a part, component or sub-system of an electronic device. Examples of electronic devices may include, without limitation, a processing system, computer, server, work station, appliance, terminal, personal computer, laptop, ultra-laptop, handheld computer, minicomputer, mainframe computer, distributed computing system, multiprocessor systems, processor-based systems, consumer electronics, programmable consumer electronics, personal digital assistant, television, digital television, set top box, telephone, mobile telephone, cellular telephone, handset, wireless access point, base station, subscriber station, mobile subscriber center, radio network controller, router, hub, gateway, bridge, switch, machine, or combination thereof. The embodiments are not limited in this context.
In some cases, various embodiments may be implemented as an article of manufacture. The article of manufacture may include a storage medium arranged to store logic and/or data for performing various operations of one or more embodiments. Examples of storage media may include, without limitation, those examples as previously provided for the memory unit 130. In various embodiments, for example, the article of manufacture may comprise a magnetic disk, optical disk, flash memory or firmware containing computer program instructions suitable for execution by a general purpose processor or application specific processor. The embodiments, however, are not limited in this context.
Various embodiments may be implemented using hardware elements, software elements, or a combination of both. Examples of hardware elements may include any of the examples as previously provided for a logic device, and further including microprocessors, circuits, circuit elements (e.g., transistors, resistors, capacitors, inductors, and so forth), integrated circuits, logic gates, registers, semiconductor device, chips, microchips, chip sets, and so forth. Examples of software elements may include software components, programs, applications, computer programs, application programs, system programs, machine programs, operating system software, middleware, firmware, software modules, routines, subroutines, functions, methods, procedures, software interfaces, application program interfaces (API), instruction sets, computing code, computer code, code segments, computer code segments, words, values, symbols, or any combination thereof. Determining whether an embodiment is implemented using hardware elements and/or software elements may vary in accordance with any number of factors, such as desired computational rate, power levels, heat tolerances, processing cycle budget, input data rates, output data rates, memory resources, data bus speeds and other design or performance constraints, as desired for a given implementation.
Some embodiments may be described using the expression “coupled” and “connected” along with their derivatives. These terms are not necessarily intended as synonyms for each other. For example, some embodiments may be described using the terms “connected” and/or “coupled” to indicate that two or more elements are in direct physical or electrical contact with each other. The term “coupled,” however, may also mean that two or more elements are not in direct contact with each other, but yet still co-operate or interact with each other.
It is emphasized that the Abstract of the Disclosure is provided to comply with 37 C.F.R. Section 1.72(b), requiring an abstract that will allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment. In the appended claims, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein,” respectively. Moreover, the terms “first,” “second,” “third,” and so forth, are used merely as labels, and are not intended to impose numerical requirements on their objects.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
|Cited Patent||Filing date||Publication date||Applicant||Title|
|US6947947||Mar 4, 2002||Sep 20, 2005||Universal Business Matrix Llc||Method for adding metadata to data|
|US7620720 *||Nov 17, 2009||Emc Corporation||Methods and apparatus for deallocation of resources|
|US20020107829||Feb 2, 2001||Aug 8, 2002||Kolbeinn Sigurjonsson||System, method and computer program product for catching, marking, managing and searching content|
|US20020143775||Feb 7, 2002||Oct 3, 2002||Wilkinson Paul D.||Multi-media management systems|
|US20030033296||Jul 17, 2002||Feb 13, 2003||Kenneth Rothmuller||Digital media management apparatus and methods|
|US20030110179||Dec 10, 2001||Jun 12, 2003||Oracle Corporation||Database system having heterogeneous object types|
|US20030115191||Jan 14, 2002||Jun 19, 2003||Max Copperman||Efficient and cost-effective content provider for customer relationship management (CRM) or other applications|
|US20030237051||May 14, 2003||Dec 25, 2003||Xerox Corporation||Clustering related files in a document management system|
|US20040024739||Jul 1, 2003||Feb 5, 2004||Kanisa Inc.||System and method for implementing a knowledge management system|
|US20050210416||Mar 16, 2004||Sep 22, 2005||Maclaurin Matthew B||Interactive preview of group contents via axial controller|
|US20060112076||Nov 19, 2004||May 25, 2006||International Business Machines Corporation||Method, system, and storage medium for providing web information processing services|
|US20070174255 *||Dec 21, 2006||Jul 26, 2007||Entrieva, Inc.||Analyzing content to determine context and serving relevant content based on the context|
|US20080016218 *||Jul 9, 2007||Jan 17, 2008||Chacha Search Inc.||Method and system for sharing and accessing resources|
|JP2005107688A||Title not available|
|KR20010098714A||Title not available|
|KR20020016056A||Title not available|
|KR20020089677A||Title not available|
|WO2005103883A1||Feb 17, 2005||Nov 3, 2005||Nervana, Inc.||System and method for semantic knowledge retrieval, management, capture, sharing, discovery, delivery and presentation|
|WO2005122023A1||May 25, 2005||Dec 22, 2005||Vital Source Technologies, Inc.||System, method and computer program product for managing and organizing pieces of content|
|WO2006026636A2||Aug 31, 2005||Mar 9, 2006||Ascential Software Corporation||Metadata management|
|WO2006036972A2||Sep 27, 2005||Apr 6, 2006||Ubmatrix, Inc.||Method for searching data elements on the web using a conceptual metadata and contextual metadata search engine|
|1||"European Search Report", Mailed Date: Jul. 8, 2011, Application No. EP/08728236, Filed Date: Jul. 7, 2011, pp. 8.|
|2||Artacho et al., "Using a High-Level Language to Describe and Create Web-Based Learning Scenarios", Date: Nov. 1999, http://sensei.lsi.uned.es/~miguel/articulos/fie99/1075. pdf#search=%22tagging%20%22heterogeneous%20objects%22%22.|
|3||Artacho et al., "Using a High-Level Language to Describe and Create Web-Based Learning Scenarios", Date: Nov. 1999, http://sensei.lsi.uned.es/˜miguel/articulos/fie99/1075. pdf#search=%22tagging%20%22heterogeneous%20objects%22%22.|
|4||International Search Report for PCT Application No. PCT/US2008/051969 mailed on Jun. 24, 2008, 2 pages.|
|5||Mathes, Adam, "Folksonomies-Cooperative Classification and Communication Through Shared Metadata", Date: Dec. 2004, http://blog.namics.com/archives/2005/Folksonomies Cooperative Classification.pdf.|
|6||Mathes, Adam, "Folksonomies—Cooperative Classification and Communication Through Shared Metadata", Date: Dec. 2004, http://blog.namics.com/archives/2005/Folksonomies Cooperative Classification.pdf.|
|7||Niederee, et al., "Taxonomies in Operation, Design, and Meta-Design", Proceedings of the Third International Conference on Web Information Systems Engineering (Workshops), Jan. 1, 2002, pp. 10.|
|8||Ohmukai et al., "A Proposal of Communicty-based Folksonomy with RDF Metadata", Retrieved from the internet on Sep. 28, 2006, 8 pages. http://www/kasm.nii.ac.jp/papers/takeda/05/ohmukai05iswc.pdf.|
|Citing Patent||Filing date||Publication date||Applicant||Title|
|US8566360 *||May 27, 2011||Oct 22, 2013||Drexel University||System and method for automatically generating systematic reviews of a scientific field|
|US8914368 *||Mar 31, 2010||Dec 16, 2014||International Business Machines Corporation||Augmented and cross-service tagging|
|US8935291 *||Oct 1, 2013||Jan 13, 2015||Drexel University||System and method for automatically generating systematic reviews of a scientific field|
|US9069802 *||Mar 17, 2014||Jun 30, 2015||Locus, LP||Syntactic tagging in a domain-specific context|
|US9245299||Jul 16, 2015||Jan 26, 2016||Locus Lp||Segmentation and stratification of composite portfolios of investment securities|
|US9361358||Jul 17, 2015||Jun 7, 2016||Locus Lp||Syntactic loci and fields in a functional information system|
|US20110246482 *||Oct 6, 2011||Ibm Corporation||Augmented and cross-service tagging|
|US20110295903 *||Dec 1, 2011||Drexel University||System and method for automatically generating systematic reviews of a scientific field|
|US20140195539 *||Oct 1, 2013||Jul 10, 2014||Drexel University||System and method for automatically generating systematic reviews of a scientific field|
|US20140280161 *||Mar 17, 2014||Sep 18, 2014||Locus Analytics, Llc||Syntactic tagging in a domain-specific context|
|Mar 26, 2007||AS||Assignment|
Owner name: MICROSOFT CORPORATION, WASHINGTON
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:TARANOV, VIKTORIYA;KOGAN, DANIEL E.;MILLER, PATRICK C.;AND OTHERS;REEL/FRAME:019060/0608
Effective date: 20070131
|Dec 9, 2014||AS||Assignment|
Owner name: MICROSOFT TECHNOLOGY LICENSING, LLC, WASHINGTON
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:MICROSOFT CORPORATION;REEL/FRAME:034542/0001
Effective date: 20141014
|Sep 23, 2015||FPAY||Fee payment|
Year of fee payment: 4